code: def use_langchain_model(
      user_prompt: str,
      model_name: str,
      temperature: float = 0.7,
      max_tokens: int = 2048,
      with_examples: bool = False,
  ) -> LLMChain:
      llm = OpenAI(
          model_name=model_name,
          temperature=temperature,
          max_tokens=max_tokens,
      )
      template, input_variables = _get_template_and_variables(
          user_prompt, with_examples=with_examples
      )
      prompt_template = PromptTemplate(
          template=template,
          input_variables=input_variables,
      )
  
      return LLMChain(llm=llm, prompt=prompt_template)
  
file_path: nebuly/optimization/chatllama/artifacts/extend_rlhf_dataset.py
imports: import os.path
  import numpy
  from langchain import OpenAI, LLMChain, PromptTemplate
  from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
label_desc: Use image node_id 2 for calling a global function with example usage: use_langchain_model(user_prompt, model_name, temperature, max_tokens, with_examples) and returns: LLMChain